A company has of transactional logs in CSV format stored in an Azure Data Lake Storage Gen2 (ADLS Gen2) account. You need to design an analytical query solution that meets the following requirements:
- Allows data analysts to run ad-hoc, exploratory T-SQL queries on the CSV files.
- Minimizes costs and administrative overhead by avoiding persistent compute resources.
- Ensures that the data remains available even if the primary Azure region suffers a complete outage.
Which two configurations should you recommend in your design?
- Query the files directly using a serverless SQL pool in Azure Synapse Analytics.Answer
- Configure the storage account to use Geo-Redundant Storage (GRS).Answer
- CProvision a Dedicated SQL pool in Azure Synapse Analytics to load and query the CSV files.
- DConfigure the storage account to use Locally Redundant Storage (LRS).
- EGenerate a Shared Access Signature (SAS) token with a three-year lifetime directly on the container to authorize the queries.
Answer
Query the files directly using a serverless SQL pool in Azure Synapse Analytics and configure the storage account to use Geo-Redundant Storage (GRS).
Using a serverless SQL pool in Azure Synapse Analytics allows you to run ad-hoc T-SQL queries directly on the CSV files in Azure Data Lake Storage Gen2 without the cost or overhead of provisioned compute. To ensure regional resilience, configuring the storage account with Geo-Redundant Storage (GRS) replicates data to a secondary region, protecting against regional outages.
Step-by-Step Solution
Key Concept
Designing cost-effective analytical storage queries and high-availability storage configurations.